Five New Machine Learning Tools To Make Your Software Intelligent

Google, Facebook, Apple, Microsoft and other tech giants standing on the bleeding edge of AI/ML innovation are actively investing in the democratization of artificial intelligence. In the recent years, these companies have open-sourced many AI/ML libraries, tools or started offering these solutions as a part of their commercial offerings and cloud services. In this article, I'm going to review five machine learning tools that have been recently released for AI startups, developers and researchers.

TensorFlow Object Detection API

Object Detection API is a new feature integrated into TensorFlow, Google’s state-of-the-art software library for machine learning. The API provides a convenient way for ML developers and researchers to identify objects in images using optimized computer vision algorithms developed at Google. Object Detection API functionality comes with the MobileNets single shot detector optimized to run on mobile devices. Designed for the limited computational and power resources of smartphones, MobileNets makes it easier for mobile developers to integrate ML functionality into their mobile applications. If you want to use AI/ML functionality in your desktop software, Object Detection API provides a heavy-duty inception-based CNN (Convolutional Neural Network) that is optimized for heavy data processing. In both cases, with Object Detection API, it becomes easier to integrate image recognition functionality into your software, which offers a great alternative to using cloud-based ML services.

Google’s Cloud Video Intelligence API

Video Intelligence API is part of Google Cloud Platform (GCP) ML services along with Google Natural Language API and Google Speech API. In a nutshell, Video Intelligence API is a suite of REST API functions that help users identify objects in videos, make videos searchable and make them discoverable. This functionality can be used to detect changes in scenes and objects and identify contexts to power video marketing, introduce interactivity into video content, detect pornographic content in the social networks or video streaming apps, label videos to generate meta-information and more. Since Video Intelligence API is provided as a REST service, there is no need to download any library or software. All you need to do is to register on the Google Cloud Platform and begin using Video Intelligence API via the standard cloud pay-as-you-go scheme.


Apple’s Core ML

In June 2017 Apple released its Core ML API designed to make AI faster on its iPhone, iPad, and Apple Watch products. The API covers all sorts of ML operations such as image and face recognition, object detection, NLP (natural language processing) and NLG (natural language generation). Core ML supports popular ML tools and models, including neural networks (deep, convolutional, recurrent), linear models and decision trees. It may be easily integrated into an Xcode development environment and become a part of your iOS app functionality. By making pre-trained ML models available for iOS developers, Apple’s Core ML promises to increase the scope of iOS applications with core AI/ML functionality available to users of Apple products. In addition, since Core ML is designed for on-device processing, it secures privacy of user data and ensures that your app is running even if a network connection is broken. In pair with the efficient on-device performance that saves memory and power consumption, Core ML strongly establishes AI/ML as a part of Apple's ecosystem.

Amazon Polly

Released in November 2016 as a part of the AWS (Amazon Web Services) artificial intelligence suite, Amazon Polly is a text-to-speech tool available as a cloud service. The service offers an easy way for users to convert text to the lifelike speech in the cloud. The system supports 24 languages and multiple voices. All you have to do is to upload the text into your AWS console, select one of 24 languages, choose your favorite voice (from seven options), customize pronunciation and download the generated audio files from the cloud to your local machine. In addition, Polly allows developers the ability to streamline the generated speech into their apps and services via an easy-to-use AWS API. This excellent tool comes absolutely free for Amazon users.

Microsoft Emotion API

Provided as a part of Microsoft Azure cloud services, Emotion API recognizes human emotions in images and videos. Emotions currently recognized by the API are anger, disgust, contempt, happiness, fear, sadness, surprise and neutrality. The API supports images featuring many faces detected using the Microsoft Face API. In addition, you can track the emotions of a person or a crowd in videos, which may be useful in detecting how people react to content or products over time. The system can recognize these emotions in near real time by extracting video frames and sending them to the API calls. To start using Microsoft’s tool, all you need to do is to send a POST or GET request to specified URLs and get JSON with a detailed description of results in response. As an alternative, Microsoft offers an SDK (software development kit) that can be integrated into your applications. The API is free for 30,000 transactions with images and 300 operations with videos per month.

Source : forbes.com